An analogy that comes to mind. It sounds a bit like neural networks are the brain's hardware (at least when squinting hard), and training large language models

An analogy that comes to mind. It sounds a bit like neural networks are the brain's hardware (at least when squinting hard), and training large language models forces the models to spend a large chunk of their training time/effort re-creating portions of the firmware. Once that's done, training on the language (or anything else) is almost trivial in comparison. That sounds quite plausible to me. It would also explain why so many people feel like this is almost a taste of AGI.